One up-to-date example of a mobile radio system is the Universal Mobile Telecommunications System (UMTS). The basic architecture of a UMTS mobile radio system has, inter alia, mobile stations (User Equipment (UE)) and a radio access network (UMTS Terrestrial Radio Access Network (UTRAN)). The radio access network contains devices for transmission of data by radio, for example base stations that are referred to as node B in UMTS mobile radio systems. The base stations each supply one specific area or a cell, in which mobile stations may be located. The interface between a mobile station and a base station whose communication takes place without the use of wires by radio is referred to as a radio interface (Uu Interface).
In a UMTS radio telecommunications system, digital data to be transmitted is first of all subjected to channel coding, in order to provide it with redundancy. The digital data is then distributed by means of a multiple access method between physical channels, within the time frame of the available transmission bandwidth. Finally, the digital data is digitally modulated in order to be transmitted via a mobile radio channel. The mobile radio channel is subdivided in time or frequency by means of a time-division duplexing method (TDD; TDD=Time Division Duplex) or a frequency-division duplexing method (FDD; FDD=Frequency Division Duplex) for transmission and reception.
The UMTS Standard and the 3GPP Standard (Third Generation Partnership Project) use the code division multiple access method (CDMA; CDMA=Code Division Multiple Access) as the multiple access method, in which a bipolar data bit stream to be transmitted is multiplied and spread by a subscriber-specific bipolar code sequence and a spreading code, respectively. The elements of the spreading code are called chips, in order to make it possible to semantically distinguish them from bits in the data bit stream. In principle, chips are nothing more than bits. The multiplication of the data bit stream by the chip stream once again results in a bipolar datastream. In general, the rate of the chip stream is a multiple of the rate of the data bit stream, and is determined by the length of the spreading code, which is indicated by a spreading factor (SF). The spreading factor corresponds to the number of chips per bit.
All of the subscribers use the multiple access method to apply a fingerprint to their payload data by means of a subscriber-specific spreading code, allowing a transmitted signal to be reproduced from a sum of received signals. The bits of the data bit stream can be recovered from the chip sequence received in the receiver by repeating the multiplication process. For this purpose, the chip stream is multiplied or correlated, once again in the correct phase, by the same spreading code that has already been used in the transmitter, from which the transmitted data bit stream is once again obtained. Different data bit streams that are intended to be transmitted in parallel from a transmitter are multiplied by different, orthogonal spreading codes or code sequences, and are then added. The sum signal is then also subjected to so-called scrambling, which is carried out by chip-by-chip multiplication of the sum signal by a specific scrambling code that, for example, identifies the base station.
Quaternary phase shift keying (QPSK) is used as the modulation method for the UMTS mobile radio system, in which two successive chips (bits) in a chip sequence to be transmitted are in each case combined to form a chip pair. One chip pair in each case forms one symbol in a symbol area (which is covered by an in-phase branch (I) and a quadrature branch (Q) of the QPSK modulation) in the complex plane, which has four elements. Since the modulation method has four values, two chips are thus in each case transmitted per modulation step. The gross chip rate is thus twice as great as the modulation rate.
In the TDD mode, a physical channel is defined by the spreading code that is used, by a time slot and by the frequency channel. In contrast, in the FDD mode, a physical channel is defined by the spreading code and by the frequency channel. A distinction is generally drawn between so-called dedicated physical channels and common physical channels. A dedicated physical channel is used exclusively by one connection and is reassigned when a connection is set up and, possibly, during the connection. Common physical channels are used by two or more connections at the same time or alternately.
In the FDD mode, physical channels are, for example, the dedicated physical channel (DPCH), the common physical control channel (CCPCH; CCPCH=Common Control Physical Channel), the common pilot channel (CPICH) and the synchronization channel (SCH). The common pilot channel CPICH is used to assist macrodiversity on the downlink path. In the case of macrodiversity, the mobile station has a radio connection to two or more base stations or cells in order, for example, to allow a soft handover, or a soft change between cells. An identical, predefined and thus known, symbol sequence is transmitted via the CPICH. Furthermore, the CPICH can thus be used to estimate channel distortion, with the aid of this known symbol sequence. The size of the CPICH is normally 6 symbols.
During operation of a mobile radio system, the mobile radio channel is characterized by multipath propagation (reflection, diffraction, scatter etc.) of the transmitted signals, time dispersion and Doppler distortion. When multipath propagation occurs, a radio signal which has been transmitted from a transmitter, for example a base station, can reach a receiver, for example a mobile station, on two or more different propagation paths, which change all the time and differ from one another by having different delay times, phase angles and levels.
FIG. 1 shows the possible propagation paths of transmitted signals in a mobile radio system using the example of signals which have been transmitted by a base station BS to a mobile station MS. Apart from a signal component on a direct propagation path W, a range of signal components which have been reflected in the far field of the receiving antenna A of the mobile station MS on obstructions H1 to H3 or, for example, on a mountain range G, reach the mobile station MS via indirect propagation paths W1 to Wn. The signal component delay is dependent on the path length differences between the individual indirect propagation paths W1 to Wn, while the levels are governed by the radio field attenuation that occurs on the corresponding propagation path. The signals that have been transmitted from a base station BS are also subject to scatter in the immediate vicinity of the mobile station MS, that is to say in the near field of the antenna A. This scatter is caused by the fact that the mobile station MS normally has an effective antenna height of about 1.5 m, while the reflective obstructions H1 to H3 in the immediate vicinity are typically higher by several factors.
The reflectivity of the surface structure of the surrounding obstructions H1 to H3 means that a wide range of accompanying, diffuse wave components, with extremely short delays between them and at levels of approximately the same magnitude reach the antenna A on the radio channel, in addition to the main wave of each signal component, which is subject to attenuation by shadowing and diffraction. Furthermore, the surface characteristics of an obstruction H1 to H3 or of the mountain range G also result in scatter at remote reflection locations, by means of which the signal components are reflected to the reception point. The mobile station MS is thus located in a dispersive field of wave components which, on average, arrive at the antenna A with a uniform distribution from all directions. The resultant sum signal for each signal component at the antenna A is obtained by vectorial addition of the wave components, while the resultant phase describes the phase angle between the direct wave and the resultant vector.
If the mobile station MS and/or the reflection locations involved are stationary, and are not moving, the level and the phase of the sum signal for each signal component does not change. However, if the mobile station MS is moving, those wave components which arrive at the antenna A from the movement direction are subject to more or less pronounced positive Doppler shifts, depending on the incidence angle. At the same time, those wave components that arrive from the opposite direction are subject to negative Doppler shifts. This symmetrical Doppler distribution necessarily leads to a relatively symmetrical Doppler spectrum on the frequency axis. The vectorial addition of the wave components and the influence of the movement of the mobile station MS mean that the different Doppler shifts of the dispersive wave components which are associated with the individual signal components lead to position-dependent, stochastic level and phase fluctuations for each signal component. These level and phase fluctuations are, however, vectorially linked to one another. The stochastic fluctuations of the signal components that are received via different indirect propagation paths are, however, uncorrelated. The distribution probability of the level fluctuations corresponds to a so-called Rayleigh distribution, and is generally referred to as Rayleigh fading, while the phase fluctuations are uniformly distributed and are referred to as parasitic phase noise (random phase noise).
A range of signal components which arrive successively in time and are caused by relatively long indirect propagation paths in the far field of the antenna A thus occur on the mobile radio channel. Owing to the near field scatter, the sum level of each signal component is subject to level fluctuations (which are independent of one another, are distributed three-dimensionally, are stochastic and are speed-dependent) and to phase fluctuations, which are correlated with them. In addition, each signal component has the Doppler spectrum, which is independent of the level fluctuation but also varies as a function of position, and whose spectral width is likewise speed-dependent. Finally, all of the signal components that are reflected in the far field are subject to a position-dependent delay with respect to the direct propagation path W, owing to the position dependency of the multipath profile.
The mobile radio channel in a mobile radio system may in general be represented by a time-variant channel impulse response h(τ, t), whose Fourier transform is the time-variant channel transfer function. The channel impulse response represents the response at the time t to an impulse at the time t−τ. The signal which is transmitted through the mobile radio channel may be represented in a receiver as the sum of a large number of waves which arrive at different times and have different levels, phase angles, polarizations and Doppler frequencies as a result of reflection, diffraction and scatter. The channel impulse response for N propagation paths is:
                                          h            _                    ⁢                      (                          τ              ,              t                        )                          =                              ∑                          n              =              1                        N                    ⁢                                          ⁢                                                                      h                  _                                n                            ⁡                              (                t                )                                      ⁢                          δ              ⁡                              (                                  τ                  -                                      τ                    n                                                  )                                                                        Equation        ⁢                                  ⁢        1            where a coefficient hn(t) represents the characteristics mentioned above of a respective propagation path n.
In order to compensate for the rotation and stretching (which occur in a mobile radio channel) of the signal received at a receiver, an estimate of the channel impulse response or channel estimation is carried out. During the channel estimation process, the coefficients of the channel impulse response are continuously matched to the channel characteristics of the individual propagation paths of the mobile radio channel in order to update the estimate. The purpose of channel estimation is to determine data from a received signal with a lower bit error rate and to know in advance the channel when data arrives at a receiver. The channel estimation process allows the disturbance influences which are typical of the method to be detected on the basis of a plausible profile of the channel characteristics, and allows reliable estimated values to be obtained for the assessment of the immediately next characters (as well as previous characters) in the payload data for each signal component, thus allowing reliable statements to be made about the mobile radio channel. Implausible discrepancies, such as those caused by noise and burst disturbances, are identified and largely eliminated. As mentioned, the mobile radio channel is a multiple path with Rayleigh fading and, in particular, with additive, physical white noise. The channel estimate is disturbed in particular by the additive white noise.
The coefficients of the channel impulse response, which are also referred to as channel coefficients, can be estimated using various solution approaches. In the simplest case, a simple low-pass filter may in each case be used for estimation of a channel coefficient for a propagation path. This low-pass filter has a cut-off frequency that corresponds approximately to the maximum Doppler frequency that occurs on the mobile radio channel. However, the Doppler frequency is not known in advance, since the relative speed of the mobile station is normally unknown.
Other solution approaches make use of a correlation of known pilot symbols (which are present in the transmitted signal) in a pilot signal with symbols from the received signal, in order to determine or to estimate the channel coefficients. A sequence of transmitted complex pilot symbols for one propagation path is referred to by p1, p2, . . . in the following text. The respective propagation path or transmission channel results in a pilot symbol pk being multiplied by a complex channel coefficient ck at a time k. Additive noise nk also occurs, so that a received symbol is in the form yk=pk*ck+nk, k=1, 2, . . . . The first step of a channel estimation process normally comprises correlation of a received symbol yk with the known pilot symbol pk, that is to say the calculation of xk:=yk/pk. When no noise is present, xk=ck, so that it is possible to speak of an unfiltered estimated value xk for the channel coefficient ck. The estimated value xk is now filtered in a second channel estimation step, in order to reduce the noise component, and the estimated value xk+1 for the channel coefficient for a subsequent time k+1 is determined at the same time. The time interval between the times is in this case, for example, chip/2. The quotient of the received and known pilot symbols in consequence results in the channel coefficient that is currently applicable to that particular propagation path (“channel snapshot”), and this is updated at the rate of the pilot symbol. The determination of the estimated value xk+1 for the channel coefficient in a subsequent time k+1, that is to say the prediction of the respective channel coefficient, makes it possible to minimize the memory required. This is due to the fact that, in contrast to the low-pass filtering process described above in which the filter delay time means that the channel state is not known until later, so that data items arriving in parallel must be stored, no data need be stored for the prediction of the channel characteristics, since the channel characteristics are known at all times from the prediction.
An FIR filter with a fixed filter length is normally used for filtering the additive white noise and for determining the estimated value xk+1 for the channel coefficient at a subsequent time k+1 and/or to calculate in advance or to predict the channel coefficient. The mobile radio channel may be derived from Equation 1 by means of a filter with a finite impulse response (FIR filter) or a tap delay line.
FIG. 2 shows an FIR filter, which represents the mobile radio channel. The coefficients hi(t) are the filter coefficients and correspond to the channel coefficients of the individual propagation paths. The first component h1(t)δ(τ−τ1) of the impulse response represents the complex signal component received via the direct propagation path, where τ1=0. Every other, delayed signal component is weighted with a complex coefficient hi(t). The delays di in this case correspond to the time interval τi−τi−1 between two successively arriving signal components.
For prediction purposes, the filter coefficients are normally constructed on the basis of an optimality criterion that is known from statistical signal theory. It is particularly useful to use so-called LMMSE estimators. These are linear estimators which minimize the mean square error (LMMSE; LMMSE=Linear Minimum Mean Square Error) and which, in this context, are also known by the name “Wiener Filters”. The performance of these Wiener filters is highly dependent on the filter length and on a previous estimate of the signal-to-noise ratio, and on the relative speed of the mobile station.
The coefficients of a Wiener filter of length N can be calculated explicitly by means of the equation:w=(Φc+N0)−1ρc  Equation 2
In this case, the matrix Φc is defined by:Φc=(J0(2πω′D(i−j)))i,j=1, . . . , N  Equation 3with the relative Doppler frequencyω′D=ωD·T=ω0·T ·υ/c  Equation 4
In this case, 1/T is the symbol rate, ω0 is the carrier frequency of the mobile radio system, v is the relative speed of the mobile station with respect to the base station, and c is the speed of light. N0 in the above Equation 2 represents the noise that is superimposed on the pilot signal, and J0 denotes the Bessel function of the first kind, which describes the characteristics of the transmission channel. The vector ρc is given by the equation:ρc=(J0(2πω′D(i0−i)))i=1, . . . , N  Equation 5
FIG. 3 shows a part of a conventional mobile radio system, from a base station to a mobile station. The direction from the base station to the mobile station is referred to as the downlink direction. The base station has transmitters S1 to Sn for payload signals x, and a transmitter SP for a pilot signal sp, for example the pilot signal in the common pilot channel CPICH in the UMTS mobile radio system. The transmitters S1 to Sn and SP are CDMA transmitters. The pilot signal is transmitted in a similar way to a payload signal, but with the difference that it can be transmitted permanently and is not modulated with payload data. The signals emitted from the transmitters S1 to Sn and SP are combined and are transmitted as the transmitted signal s via a multipath transmission channel CH, which is the same for all the signals and is in the form of a mobile radio channel in the present example. At the receiving end, that is to say in the mobile station, a receiving unit EE recovers the transmitted payload signals x′ from a received signal r, and passes them to a data sink.
The payload data x1 emitted from a data source DQ1 is spread in a spreading stage SS1 in the transmitter S1 using a spreading code SC1 from a spreading code generator SG1, and is emitted as the transmitted signal s1. The transmitted signal s1, which has been spread by the spreading factor, is combined with further transmitted signals which may be present and with the pilot signal sp, which has been spread in a corresponding manner by means of a spreading code, and is emitted as the transmitted signal s. On the multipath transmission channel CH, the transmitted signal s is subject to time-variant influences Z, which result from the multipath propagation of the schematically illustrated radio field FF, to radio interference or disturbances F, which may occur in the form of pulsed, burst or continuous disturbances, and to the influence of noise R. The transmitted signal s is also subject to distance-dependent attenuation in the radio field FF. In the receiving unit EE in the mobile station, the received signal r is correlated with the spreading code of the pilot signal sp and with a correlation code which corresponds to the spreading code, for example SC1, in order to recover the pilot signal on the one hand, and the payload signals x′ on the other hand.
In order to reproduce the transmitted signal from a received signal r which is composed of a superimposition of signal components transmitted on the various propagation paths, it is processed in the receiving unit EE in the mobile station by means of a RAKE receiver. The RAKE receiver has fingers, which are each associated with one propagation path and are operated with a sampling delay that compensates for the delay on the corresponding propagation path. Each finger has a correlator which multiples the delayed signal component from one propagation path by a spreading code, in order to reproduce bits from the signal component which was spread at the transmitter end using the same spreading code. The output signals from the individual fingers are combined or coherently added, in order to gather the energy per symbol not only via a direct propagation path but also from a large number of indirect propagation paths, and thus to improve the communication reliability. The coherent addition process is also referred to as maximum ratio combining.
FIG. 4 shows a RAKE receiver that is contained in the receiving unit EE. The received signal r is correlated in a correlator K1 in the RAKE receiver with a correlation code that is matched to the spreading code of the pilot signal sp. A complex output signal from the correlator K1 is supplied to a channel estimator KS. The received signal r is also correlated in a correlator K2 with correlation codes that are matched to the correlation codes SC1 of the payload signals xi. A RAKE combiner RC carries out the coherent addition process with the signal emitted from the correlator K2 and the channel information emitted from the channel estimator KS. A downstream decision stage E uses, for example, the QPSK method to demodulate the received payload signal x′ associated with the transmitted payload signal.
The channel estimator KS calculates estimated values for the channel coefficients. The estimated values control the coherent addition of the signals obtained in the correlator K2, in the RAKE combiner RC. During the estimation of the channel coefficients, the following measures must be carried out continuously:                identification of significant signal components;        estimation of the associated delay times or delays; and        estimation of the associated complex amplitudes or levels.        
FIG. 5 shows a schematic illustration of a time signal at the output of the correlator K1. All the values and correlation peaks of a delay τi at the time interval T are used to estimate a channel coefficient for one propagation path. The correlation peaks for the delay τi are marked by arrows.
FIG. 6 shows the design of a conventional channel estimator KS. The output signal from the correlator K1 shown in FIG. 4 is sampled at the time interval of a chip Tc. The values obtained in this way are stored at the chip rate 1/Tc in a shift register SR. Each individual cell in the shift register SR produces values for in each case one estimator S1 to SN that is associated with one propagation path. When the values stored in the shift register SR are processed, they are shifted onwards by the time period T. A signal for that propagation path which has the same delay τi is thus always applied to an estimator S. The estimators S each estimate one channel coefficient on the basis of the correlation peaks for an associated propagation path in FIG. 5. The estimators S furthermore predict the channel coefficients for a subsequent time, by means of a Wiener filter.
One disadvantage of the Wiener filter that is normally used for a prediction of channel coefficients is that the explicit calculation of the filter coefficients is complex.
A further disadvantage of the Wiener filter is that the filter coefficients depend in a complex manner on the signal-to-noise ratio and on the speed.
A further disadvantage of the Wiener filter is that the filter coefficients must be recalculated with each symbol for an exact implementation of the MMSE method so that, in practice, suboptimal variants of Wiener filtering must normally be chosen, in order to simplify the calculation.